Artificial intelligence as a personal development tool: Offline tools useable in Microsoft environments
Olli Kauppinen · Theseus (Ammattikorkeakoulujen) · 2026
Integration of artificial intelligence has become a transformative force in software development, with tools helping people to write code and test code automatically. While cloud-based solutions are more widely available at a low to no cost, today’s computer technology allows open-source local models to be taken into use. Local models offer self-hosted environments without sending any information to remote locations, adding a cybersecurity aspect to workflows. However, practical knowledge required to set up, integrate and effectively use local models remains a significant barrier to many students and developers. This thesis aims to give practical application example of leveraging local models within private environment. Primary object of this research is to demonstrate how to successfully implement and leverage local AI models in Microsoft Windows environment. The study will provide a detailed walkthrough of configuring models to be part of software development cycle and integrating into everyday use. To contextualize the capabilities and limitations of this approach, the performance and output of the local models will be benchmarked against free, web-based solutions. Thesis is limited to use available models, but not to train with own data. Expected outcome is a set of practical guidelines for people seeking to adopt use of local AI, highlighting advantages of local models in terms of data privacy, control and offline functionality